Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Found insideLeverage the power of Scala with different tools to build scalable, robust data science applications About This Book A complete guide for scalable data science solutions, from data ingestion to data visualization Deploy horizontally ... Found insideBecome an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data ... This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it. If you are a Scala, Java, or Python developer with an interest in machine learning and data analysis and are eager to learn how to apply common machine learning techniques at scale using the Spark framework, this is the book for you. GraphX gives you unprecedented speed and capacity for running massively parallel and machine learning algorithms. About the Book Spark GraphX in Action begins with the big picture of what graphs can be used for. Found insideThis book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. Found insideThis book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Found insideThis book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. A concise guide to implementing Spark Big Data analytics for Python developers, and building a real-time and insightful trend tracker data intensive appAbout This Book- Set up real-time streaming and batch data intensive infrastructure ... Found inside – Page 1In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility. Found insideIf you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Found insideAbout This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with ... Found inside – Page iThis book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation. Found insideDesign, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning ... Found insideBuild, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of ... "This book is about the fundamentals of R programming. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. Found inside – Page iiThis book covers the five main concepts of data pipeline architecture and how to integrate, replace, and reinforce every layer: The engine: Apache Spark The container: Apache Mesos The model: Akka“li>The storage: Apache Cassandra The ... Found insideWith this book, you’ll explore: How Spark SQL’s new interfaces improve performance over SQL’s RDD data structure The choice between data joins in Core Spark and Spark SQL Techniques for getting the most out of standard RDD ... This book contains 33 chapters contributed by Brian Kernighan, KarlFogel, Jon Bentley, Tim Bray, Elliotte Rusty Harold, Michael Feathers,Alberto Savoia, Charles Petzold, Douglas Crockford, Henry S. Warren,Jr., Ashish Gulhati, Lincoln Stein, ... Found insideYou’ll find comprehensive coverage on key features such as the Pig Latin scripting language and the Grunt shell. When you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig. Jeannette Walls was the second of four children raised by anti-institutional parents in a household of extremes. The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. This book teaches you the different techniques using which deep learning solutions can be implemented at scale, on Apache Spark. This will help you gain experience of implementing your deep learning models in many real-world use cases. Found inside – Page iCarry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. Found inside – Page iThis book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. In it, you'll find concrete examples and exercises that open up the world of functional programming. This book assumes no prior experience with functional programming. Some prior exposure to Scala or Java is helpful. Found inside – Page iiSo reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Found insideThis book covers the fundamentals of machine learning with Python in a concise and dynamic manner. This book will help you perform effective data analysis with Scala using practical examples. Found insideWith this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Found insideWhat you will learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and ... Found inside – Page iThis book constitutes the proceedings of the workshops of the 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2016, held in Grenoble, France in August 2016. Found insideLearn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. Found insideWhat you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more ... Found insideWith this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades. About the Book Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Furthermore, at the end of the book, we will dive into some advanced concepts such as MTL, Classy Optics and Typeclass derivation. Found inside – Page iWhat You Will Learn Understand the advanced features of PySpark2 and SparkSQL Optimize your code Program SparkSQL with Python Use Spark Streaming and Spark MLlib with Python Perform graph analysis with GraphFrames Who This Book Is For Data ... In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. Found inside – Page iBy the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. 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